Add ast_churn: port of Go's garbage benchmark - #103
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Repeatedly parse Julia source from Base with Meta.parseall on 2*nthreads
concurrent tasks, keeping a rotating window of parsed ASTs alive so half the
window behaves as an old generation. This is a port of Go's `garbage`
benchmark (golang/benchmarks/garbage), the workload used to motivate the
Green Tea collector.
Unlike the binary-tree benchmarks, an AST is a graph of many different small
types (Expr, Symbol, LineNumberNode, Vector{Any}), so the mark phase cannot
assume neighbouring objects share a layout - a heterogeneous-heap stress test
the suite currently lacks. On a Zen 4 machine with 4 threads it runs ~9s with
~22% of time in GC.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
oscardssmith
approved these changes
Aug 4, 2026
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Port of Go's
garbagebenchmark (golang/benchmarksgarbage/garbage.go), the GC-heavy workload used to motivate the Green Tea collector.2 * nthreadstasks repeatedly parse ~10 files of Base source withMeta.parseall, keeping a rotating window of 64 parsed ASTs alive; only the first half of the window is overwritten, so the second half behaves as an old generation (as in the Go original).Why it earns a slot in the suite: an AST is a deep pointer graph of many different small types (
Expr,Symbol,LineNumberNode,Vector{Any}, literals), so the mark phase cannot assume neighbouring objects share a layout. That heterogeneous-heap profile is what package loading and tooling workloads look like, and no current benchmark has it — the binary-tree and array benches are homogeneous. While characterizing mark-phase experiments on julia master we found this workload consistently responds differently from every synthetic benchmark in the suite, which is exactly why it's worth tracking.Measured on Julia 1.12.6, 4 threads (Zen 4): ~9 s, ~6 GB allocated, ~22% of time in GC.
Disclosure: this PR was written with the assistance of generative AI (Claude).
🤖 Generated with Claude Code